We are seeking a talented and driven Computer Vision Engineer to join our dynamic team. The ideal candidate will be proficient in Python development with a strong background in computer vision algorithms, deep learning frameworks, and image processing techniques. You will collaborate with our core development team to design, implement, and optimize computer vision models and systems that enhance user experiences across various applications.
Key Responsibilities
- Develop, test, and maintain computer vision algorithms and applications.
- Collaborate with the development team to integrate computer vision solutions into broader software projects.
- Write clean, scalable, and efficient code following best practices in Python and computer vision.
- Debug and troubleshoot issues related to computer vision models and their integration with software systems.
- Participate in code reviews and provide constructive feedback to peers.
- Create and maintain technical documentation, including model design, architecture, and performance metrics.
Qualifications
- Strong proficiency in Python 3.10.
- Proficiency in computer vision libraries such as OpenCV, YOLOv8, SAMv2, and others.
- Experience with deep learning frameworks like TensorFlow, PyTorch, or similar.
- Experience with image processing techniques and tools.
- Familiarity with Websockets and their integration with computer vision models.
- Proficiency in version control tools, particularly GitHub.
- Familiarity with model deployment frameworks such as Gradio, Mesop, Streamlit, or similar.
- Experience with containerization and orchestration tools like Docker and Kubernetes (a plus, but not necessary).
- Understanding of hardware acceleration (e.g., GPUs) for computer vision tasks (a plus, but not necessary).
Preferred Skills
- Ability to work in a fast-paced environment and manage multiple projects simultaneously.
- Strong problem-solving skills and attention to detail, particularly in the context of computer vision challenges.
- Excellent communication skills and ability to collaborate effectively with cross-functional teams.